In recent years, physiological signals have also demonstrated great potential in authenticating individuals. Physiological signals are in fact more preferable to other means of authentication as they are hard to counterfeit and also the individuals need to present themselves to record such signals [1]}. Among various physiological signals electrocardiogram (ECG) [2]}, electroencephalography (EEG) [3]} and photoplethysmography (PPG) [4]} are the most prominent. Compared to most physiological signals, PPG and ECG signals can be obtained relatively easily, for example, using simple finger sensors [5]}. Furthermore, ECG signals are more resilient against noises, compared to PPG or EEG, which has made ECG more preferable as a biometric system [6]}. As a result ECG bands [7]}, low power circuits [8]} and light-weight algorithms [9]} have been developed for ECG based authentication systems. Furthermore, with the recent introduction of ECG sensors in commercial products like the Apple Watch and Samsung Galaxy Watch, the possibility of widespread adoption of ECG biometrics has opened [10]}.
